AI and the Future of Work: Artificial Intelligence in the Workplace, Business, Ethics, HR, and IT for AI Enthusiasts, Leaders and Academics

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Arnnon Geshuri is Chief People Officer at Snowflake, where he leads culture development, talent strategy, and organizational design at one of the world’s leading data cloud companies. His career spans decades of scaling high-growth technology organizations, including leadership roles at Google, Livongo Health, and Tesla, where he oversaw its growth from a 400-person startup to a 35,000-person transportation juggernaut.
Throughout his career, he has consistently chosen companies that demand a people function as innovative, as creative, and as forward-thinking as the business itself. And across every role, he has focused on one core idea: the people function must evolve as fast as the business itself, grounded in data, experimentation, and trust.
In this episode, Arnnon draws on that experience to challenge how leaders think about AI in the workplace, arguing that the real opportunity is not automation alone, but redefining how humans contribute, decide, and grow inside modern organizations.

In this conversation, we discuss:
Why the people function must speak the language of data and analytics to influence engineering-led organizations and earn credibility in high-growth, technical environments
The shift from transactional HR to a strategic role focused on connection, education, and rebuilding trust after workforce disruption and disconnection during COVID
How Snowflake frames AI adoption by automating repetitive work, augmenting creative tasks, and preserving human judgment in decisions that require empathy and context
Why employees adopt AI faster when leaders encourage curiosity, remove fear of experimentation, and make tools accessible through simple interfaces like natural language
The risks of over-automating decisions like hiring and performance reviews, and why removing human accountability breaks trust inside organizations
How building a culture of experimentation, measurement, and iteration allows people leaders to scale organizations without relying on intuition alone

Explore the Conversation
00:00 Intro & Fun Fact: How AI manipulation threatens autonomy
05:06 Meet Arnnon Geshuri: CPO at Snowflake, from Google, Tesla, and Livongo Health
10:24 The Evolution of HR: From Transactions to Amplifying Humanity
13:37 Snowflake's AI Framework: Automate, Augment, and Preserve Human Judgment
21:44 Driving AI Adoption: AI for Everybody and a Culture of Experimentation
26:26 Data Privacy and Trust: Building Guardrails for Enterprise AI
28:36 AI in Hiring: Mitigating Bias to Rescue Human Connection
32:28 Setting AI Boundaries: Why Algorithms Should Never Conduct Performance Reviews
34:16 Scaling Culture in Hyper-Growth: The Power of People Analytics
41:33 The AI Ride-Along Prediction and What Comes Next
43:15 Where to Connect with Arnnon Geshuri and Snowflake

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On How Rodrigo Liang, Raised Over $1B to Build the First Generative AI Unicorn

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In this special episode of AI and the Future of Work, we are bringing you an exclusive conversation recorded live on the show floor at the HumanX 2026 event. This full interview kicks off a special three-part series, with the upcoming two episodes releasing in a compilation format. To start things off, we are sharing our uncut conversation with the man who made this entire gathering possible.
Stefan Weitz is the Co-founder and CEO of HumanX, an organization and premier event dedicated to cutting through the AI hype to find practical, world-changing applications. He joined Microsoft in 1996, working alongside leaders like Bill Gates and Steve Ballmer on iconic product launches and foundational tech like Bing and Windows.
In this live episode, Stefan draws on his extensive product development background to explain why our survival in the AI era depends on treating technology as an evolving tool and why the most powerful thing a leader can say today is "I do not know".
In this conversation, we discuss: 
Why relying on focus groups and lean product development is the wrong approach for building breakthrough AI hardware and software.
The reason established tech giants risk losing the AI race if they rely solely on distribution over building superior products.
How AI differs fundamentally from all previous human tools and why its ability to learn creates unprecedented exponential growth.
Why the speed of current technological adaptation threatens to outpace our natural ability to transition roles and find new purpose.
The danger of anthropomorphizing artificial intelligence and why framing it as human creates unnecessary fear and resistance.
How saying "I do not know" has become the most powerful leadership tool in a non-deterministic technology landscape.
Resources:
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Robb Wilson is the CEO and co-founder of OneReach.ai, an agent-building platform focused on complex enterprise use cases across healthcare, government, and telecommunications. A serial entrepreneur and former creative executive at Time Warner, Robb has spent decades working at the intersection of design and technology. He is also the co-owner of UX Magazine, a global community of more than 640,000 members, and the author of two bestselling books, including Age of Invisible Machines.
His career spans designing high-stakes systems like the Boeing 787 cockpit to building conversational AI platforms that rethink how humans interact with technology. Along the way, he earned an Academy Award nomination for Technical Achievement, reflecting his ability to bridge creativity and engineering at scale.
In this episode, Robb draws on that rare combination of design, product, and systems thinking to challenge how companies are adopting AI today, and why most are optimizing the wrong layer of the problem.

In this conversation, we discuss:
Why companies are using AI to accelerate outdated software instead of rethinking what software should be, and how this creates the illusion of progress without meaningful change
The fundamental mismatch between human communication and traditional interfaces, and why conversational interaction exposes how poorly most software has been designed for real users
What “getting AI” actually means inside organizations, and why productivity gains often hide the fact that teams are still building systems they plan to replace
The concept of “invisible machines” and why the future of AI is not better interfaces, but removing interfaces entirely to prioritize human interaction over system interaction
Why evaluating AI systems based on what they do misses the point, and how understanding how they learn becomes the more critical question for decision-makers
The tension between building AI that drives engagement versus AI that strengthens human connection, and how market incentives continue to reward the wrong outcomes

Explore the conversation:
00:00 Intro and Fun Fact 
04:27 Robb Wilson's Journey at the Intersection of Design and Technology
06:26 The UX Collision: Why Using AI to Build Old Software Faster is a Mistake
10:47 Defining Human-First Design and the Concept of Invisible Machines
13:26 Lessons from the Boeing 787: Using Context to Remove Complex Interfaces
16:08 The Adoption Problem: Why We Must Evaluate How AI Software Learns
20:40 The OpenAI Dilemma: Choosing Between Dopamine-Driven AI and Healthy Innovation
25:22 The End of Compiled Software: Why True AI Transformation Requires Total Transparency
29:48 Future Interfaces: Valuing Human Connection Over Brain Chips and Productivity
35:09 Will Capitalism Reward Ethical AI? The Power of Consumer Choice
41:54 Where to Connect with Robb Wilson and OneReach.ai

Resources
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On How Steve Truitt Is Working to Save Humanity and Prevent AI From Ruining Us

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Matt Fitzpatrick is the CEO of Invisible Technologies, an AI platform used to improve models for more than 80% of the world’s leading AI companies, including Microsoft, AWS, and Cohere. The company has raised $100 million and scaled to $134 million in revenue, making it one of the fastest-growing AI companies globally.
Before joining Invisible, Matt was the Global Head of QuantumBlack Labs at McKinsey, where he led large-scale AI and data engineering efforts and helped enterprises move from experimentation to production.
In this episode, Matt draws on years spent inside enterprise AI deployments to challenge the gap between model progress and real-world adoption, and to explain why most organizations still struggle to turn AI into measurable business outcomes.

In this conversation, we discuss:
Why enterprise AI adoption lags far behind model performance improvements, and why most organizations still struggle to turn technical progress into real business impact
The hidden role of messy, fragmented legacy data, and why decades of accumulated systems make it nearly impossible to deploy reliable AI at scale
Why defining “good” output in generative AI is far harder than expected, and how unclear standards stall deployment across high-stakes enterprise workflows
The case for redesigning workflows from scratch, and why layering AI on top of existing processes fails to create meaningful efficiency gains
Why most AI initiatives fail due to lack of business ownership, and how separating technology teams from operators prevents projects from reaching production
How fear-driven narratives about job loss are slowing adoption, and why AI is more likely to shift work toward higher-value tasks than eliminate roles entirely
 
Explore this conversation: 
00:00 Intro and Fun Fact 
03:57 Matt Fitzpatrick's Path From McKinsey to Invisible Technologies 
09:56 Scaling Enterprise AI with Modular Platforms and Clean Data 
12:44 The Crucial Role of Expert Human Feedback in Model Training 
17:56 Why 95% of Enterprise AI Projects Never Reach Production
21:38 The Missing Link: Why True AI Transformation Requires Business Ownership 
26:54 Overcoming AI Fear and the Reality of Jevons Paradox 
32:24 Responsible AI: Governing Outcomes Over Technology 
39:05 The Future of Work: Moving From Administration to Innovation 
44:12 Where to Connect with Matt Fitzpatrick and Invisible Technologies

Resources:
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Connect with Matthew on LinkedIn
AI fun fact article
On How Allison Baum Gates Reveals the Secrets to a Successful VC Career

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Your employees are already ahead of you on AI. The data is in and the question is no longer whether this is happening, but what leaders choose to do about it.
That is one of the key findings from Microsoft's 2026 Work Trend Index, and it is the starting point for this week's special episode. PeopleReign CEO Dan Turchin sits down with Matt Firestone, General Manager at Microsoft leading product marketing for Microsoft 365 Copilot and Agents, to unpack what trillions of anonymized signals across the Microsoft 365 ecosystem reveal about how AI is actually changing work right now.
What pairing telemetry with survey responses and in-house research reveals about the gap between where employees actually are and where their organizations think they are is striking. And the numbers on how organizations reward, or fail to reward, the people already doing this work will make most leaders uncomfortable. The bottleneck, it turns out, isn't where most people expect it.
In this conversation, we discuss:
Why the job of a leader has shifted from designing transformation strategy to changing systems and culture
How the report reframes agentic AI collaboration, not as a threat to human agency, but as an expansion of it
What "frontier firms" and "frontier professionals" actually means, and why it's a mental model and rallying cry, not a marketing term
How building in the open, leaders experimenting visibly and removing the stigma of getting things wrong, is one of the most quantifiably impactful things a manager can do
Why agent adoption on the Microsoft 365 ecosystem is growing at a rate that will surprise even the optimists
Explore this conversation:
00:00 Intro
01:14 Inside Microsoft’s 2026 Work Trend Index
02:22 Telemetry, Not Just Surveys: What the Data Reveal
03:09 Employees Are Ahead of Their Managers on Agentic AI
04:37 The Transformation Paradox and Broken Reward Systems
06:15 More Agentic AI, More Human Agency: The 49% Finding
09:28 How Leaders Should Respond: Build in the Open
11:26 Safety, Trust, and Responsible AI at Microsoft Scale
13:36 Building a Manager Equity Dashboard in 25 Minutes with Copilot
17:31 What Frontier Firms and Frontier Professionals Actually Do
20:04 AI, Toil, and the Fear of Becoming Obsolete
22:52 The 1 Billion Agents Prediction and What Comes Next

Resources
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Microsoft's 2026 Work Trend Index